The subject matter disclosed herein relates to the field of image processing and, without limitation, techniques for improving disparity estimation using sparsely-distributed phase detection (PD) pixels.
The process of estimating the depth of a scene from two viewpoints is commonly referred to as stereoscopic vision and, when using multiple viewpoints, multi-view stereo. In practice, many camera systems use disparity as a proxy for depth. (As used herein, disparity is taken to mean the difference in the projected location of a scene point in one image compared to that same point in another image captured.) Generally, disparity can be considered the inverse of depth, such that disparity is equal to 1/depth. Depth information can be obtained using active depth sensing hardware, such as radar, lidar, time of flight cameras, structured light projectors, and the like. Depth information can also be obtained for a scene by a camera system by obtaining stereo camera images of the scene from different viewpoints and determining the disparity between the images. Camera systems with multiple cameras are often used to capture images from different viewpoints. Camera systems with a single camera can also be configured to capture images from different viewpoints, such as by physically moving the camera system, or using a different set of sensor pixels of a camera to capture the different viewpoints. With a geometrically calibrated camera system, disparity can be mapped to scene depth. The fundamental task for such camera-based depth estimation systems then is to find matches, or correspondences, of points between images from two or more images captured by the camera system of the same scene.